School of Agriculture, Food and Ecosystem Sciences - Research Publications
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ItemNo Preview AvailableThe effects of junction fire development on thermal behaviour at the field scale(ELSEVIER SCI LTD, 2024-02)
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ItemNo Preview AvailableMulti-scale investigation of factors influencing moisture thresholds for litter bed flammability(ELSEVIER, 2023-06-15)Fuel moisture is important to flammability. Vegetation communities vary in their moisture thresholds for ignition and fire spread. Different factors, operating at distinct spatial scales (litter vs. vegetation community) may be responsible for these variations in moisture thresholds. The relative importance of these factors at each scale remains unquantified. Our study sought to examine what factors influence moisture thresholds for flammability across two spatial scales (point vs. plot). Litter samples were collected repeatedly over one fire season (2020–21) from selected sites within temperate eucalypt forest along an aridity gradient in south-eastern Australia. Samples were reconstructed then burnt under controlled conditions. At the point-scale (0.05 m²), we quantified flammability as the probability of sustained ignition, flame spread rate and flaming duration. At the plot-scale (400 m²), we quantified flammability as the proportion of sustained ignitions. At the point-scale, moisture thresholds varied with leaf cover on the surface of the litter bed for ignition and leaf size for flame spread rate. At the plot-scale, vapour pressure deficit (VPD) was the best predictor of ignitability and moisture thresholds varied with aridity. Wetter parts of the landscape had a higher VPD threshold for ignition than more arid parts, meaning they were available to burn less often. The relationship between leaf cover and ignitability observed at the point-scale was overwhelmed by the effect of moisture at the plot-scale. Variations in ignitability between vegetation communities were driven by aridity-induced changes in canopy cover and its effect on litter moisture. Ignitability models based on VPD and aridity could be used to predict ignitability now and into the future, given anticipated increases in VPD under climate change.
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ItemLeaf traits predict global patterns in the structure and flammability of forest litter beds(WILEY, 2021-03)Fallen plant material such as leaves, needles and branches form litter beds which strongly influence fire ignition and spread. Traits of the dominant species influence litter flammability directly by determining how individual leaves burn and indirectly through the structure of the litter bed. However, we are yet to determine the relative importance of these different drivers across a range of plant species from different biomes. We undertook a meta‐analysis, combining leaf trait, litter structure and flammability data for 106 species from North America, South America, Europe, Asia and Australia. The dataset encompassed broad‐leaved and coniferous species from seven different experimental studies. Relationships between leaf traits, litter structure and key flammability metrics—sustainability, combustibility and consumability—were analysed using bivariate and piecewise structural equation modelling (SEM). Traits which characterise the three‐dimensional nature of the leaf and how much space a leaf occupies showed much stronger associations to litter structure and flammability than other morphological traits. Leaf curl, surface area to volume ratio (SAV) and SLA predominately influence litter flammability indirectly via litter structure with SLA being the only leaf trait which had a negative direct effect on flame duration. Packing ratio and bulk density were influenced by different combinations of leaf traits and, in turn, they aligned with different flammability metrics. Bulk density predicted flame spread rate and flame duration whereas packing ratio predicted consumption. Synthesis. We identified key leaf and litter traits which influence different components of litter bed flammability. Importantly, we show that the effects of these leaf and litter traits are consistent across a wide range of taxa and biomes. Our study represents a significant step towards developing trait‐based models for predicting surface wildfire behaviour. Such models will more flexibly accommodate future shifts in the composition of plant species triggered by altered fire regimes and climate change.
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ItemQuantifying merging fire behaviour phenomena using unmanned aerial vehicle technology(CSIRO PUBLISHING, 2020-12-10)Catastrophic wildfires are often a result of dynamic fire behaviours. They can cause rapid escalation of fire behaviour, increasing the danger to ground-based emergency personnel. To date, few studies have characterised merging fire behaviours outside the laboratory. The aim of this study was to develop a simple, fast and accurate method to track fire front propagation using emerging technologies to quantify merging fire behaviour at the field scale. Medium-scale field experiments were conducted during April 2019 on harvested wheat fields in western Victoria, Australia. An unmanned aerial vehicle was used to capture high-definition video imagery of fire propagation. Twenty-one junction and five inward parallel fire fronts were identified during the experiments. The rate of spread (ROS) of junction fire fronts was found to be at least 60% higher than head fire fronts. Thirty-eight per cent of junction fire fronts had increased ROS at the final stage of the merging process. Furthermore, the angle between two junction fire fronts did not change significantly in time for initial angles of 4–14°. All these results contrast with previous published work. Further investigation is required to explain the results as the relationship between fuel load, wind speed and scale is not known.
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ItemFrequency of Dynamic Fire Behaviours in Australian Forest Environments(MDPI, 2020-03)Wildfires can result in significant social, environmental and economic losses. Fires in which dynamic fire behaviours (DFBs) occur contribute disproportionately to damage statistics. Little quantitative data on the frequency at which DFBs occur exists. To address this problem, we conducted a structured survey using staff from fire and land management agencies in Australia regarding their experiences with DFBs. Staff were asked which, if any, DFBs were observed within fires greater than 1000 ha from the period 2006–2016 that they had experience with. They were also asked about the nature of evidence to support these observations. One hundred thirteen fires were identified. Eighty of them had between one and seven DFBs with 73% (58 fires) having multiple types of DFBs. Most DFBs could commonly be identified through direct data, suggesting an empirical analysis of these phenomena should be possible. Spotting, crown fires and pyro-convective events were the most common DFBs (66%); when combined with eruptive fires and conflagrations, these DFBs comprise 89% of all cases with DFBs. Further research should be focused on these DFBs due to their high frequencies and the fact that quantitative data are likely to be available.
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ItemImproving Fire Behaviour Data Obtained from Wildfires(MDPI, 2018-02)Organisations that manage wildfires are expected to deliver scientifically defensible decisions. However, the limited availability of high quality data restricts the rate at which research can advance. The nature of wildfires contributes to this: they are infrequent, complex events, occur with limited notice and are of relatively short duration. Some information is typically collected during wildfires, however, it is often of limited quantity and may not be of an appropriate standard for research. Here we argue for a minimum standard of data collection from every wildfire event to enhance the advancement of fire behaviour research and make research findings more internationally relevant. First, we analyse the information routinely collected during fire events across Australia. Secondly, we review research methodologies that may be able to supplement existing data collection. Based on the results of these surveys, we develop a recommended list of variables for routine collection during wildfires. In a research field typified by scarce data, improved data collection standards and methodologies will enhance information quality and allow the advancement in the development of quality science.